About Me
I'm a Data Engineer and Machine Learning specialist passionate about turning raw, fragmented data into scalable, intelligent systems. With an M.Sc in Data Science from the University of Surrey, I combine hands-on engineering skills with applied machine learning expertise to build solutions that are both robust and insightful.
My experience spans end-to-end data workflows, from data ingestion, transformation, and orchestration to model training, evaluation, and deployment. I work extensively with Python, SQL, and modern data platforms such as AWS, Databricks, and Airflow, ensuring reliable and high-performing data pipelines.
I'm particularly interested in how data infrastructure, ML models, and intelligent agents intersect, creating systems that not only analyse information but act on it.
Whether it's designing ETL architectures, optimizing data quality, or building machine learning models for prediction and automation, my goal is to engineer systems that make data truly work for people and organizations.
Data Engineering
Designing ETL pipelines, database optimization, and cloud data solutions
Machine Learning & AI
Building intelligent solutions with Python, NLP, and deep learning frameworks
AI Engineering
Developing LLM applications, RAG systems, and AI-powered solutions with vector databases
Featured Projects
A collection of my work across machine learning, data engineering, and AI applications
Prompt Enhancer
Chrome extension using Google's Gemini Nano AI for on-device prompt enhancement. Enhances ChatGPT prompts instantly with 100% local processing, zero API costs, and complete privacy.
Other Projects
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Technical Skills
A comprehensive toolkit spanning data science, machine learning, and software development
Programming Languages
Machine Learning & AI
Data Engineering
Cloud & DevOps
Data Visualization
Currently Expanding
Cloud Certifications
AWS & GCP certifications
MLOps & Deployment
CI/CD for ML models, experiment tracking
LLM & Agent Systems
Building AI agents, RAG pipelines, tool-augmented LLMs
Real-time Systems
Streaming data & live dashboards
Current Learning Interests
I'm continuously exploring where data engineering, machine learning, and intelligent systems converge. Here's what drives my learning journey:
Scalable Data Systems
Designing and building reliable data platforms, distributed architectures, and high-throughput pipelines that handle real-world data at scale.
Applied Machine Learning
Developing ML models for real-world prediction, automation, and decision support, spanning NLP, computer vision, and time-series forecasting.
AI Agents & LLM Systems
Building intelligent systems that reason, plan, and act autonomously using large language models, retrieval-augmented generation, and tool-use architectures.
Financial Data & Analytics
Applying data engineering and analytics to financial datasets, exploring market trends, and building data-driven insights for investment and risk analysis.
How I'm Learning
Technical Reading
Staying current with data engineering, ML research, and system design literature
Online Courses
Deepening expertise through ML, data engineering, and cloud platform courses
Hands-on Projects
Building real-world applications to apply concepts in practice
Blog & Insights
Writing about AI, data, and how these tools actually work behind the scenes—now live on Medium.
Latest on Medium
Prompt Enhancer Chrome Extension with Gemini Nano
Demystifying AI Tools: How They Work Under the Hood
Over the last few weeks, I've been building a Chrome extension called Prompt Enhancer that turns rough ideas into clear, structured prompts for ChatGPT in a single click. It runs fully on-device using Chrome's built-in Gemini Nano via the Prompt API, so nothing ever leaves your browser.
What you can expect
Data & ML
How data engineering and machine learning solve real-world problems
AI Tools & Systems
Breaking down how modern AI tools work under the hood
Data Engineering
Pipelines, architectures, and practical implementations
💡 Get notified: Follow @pranavakailash on Medium to receive updates when new breakdowns of AI tools and data workflows go live.
Let's Connect
I'm open to opportunities in data science, machine learning, and data engineering. Let's discuss how I can contribute to your team.
Get In Touch
Open To Opportunities
Data Engineering
Building scalable data pipelines and platforms
Machine Learning Engineer
Developing and deploying ML models at scale
Data Science Roles
Extracting insights through statistical analysis and ML
AI/ML Solutions
End-to-end AI systems from data to deployment